Despite extensive research efforts in recent years, computational argumentation (CA)
remains one of the most challenging areas of natural language processing. The reason for …

Argument mining involves multiple sub-tasks that automatically identify argumentative
elements, such as claim detection, evidence extraction, stance classification, etc. However …

The aim of this work is to employ Tree Kernel algorithms to classify natural language in the
legal domain (ie deontic sentences and rules). More precisely, an innovative way of …

This work describes a simple Transfer Learning methodology aiming at discriminating
evidences related to Argumentation Schemes using three different pre-trained neural …

The aim of this study is to propose an innovative methodology to classify argumentative
stances in a monologic argumentative context. Particularly, the proposed approach shows …

The approach proposed in this study aims to classify argumentative oppositions. A major
assumption of this work is that discriminating among different argumentative stances of …

This paper describes a long-term research goal which aims at creating a middleware
interface between Argumentation Schemes and natural language. This idea comes from the …

This work investigates how the combination of different tree representations with different
Tree Kernel functions influences the results of the classifications in two specific case studies …

In this paper, we propose the formalisation of a new argu-mentation scheme for the domain
of legal argumentation, which we call Argument from Vicarious Liability. This scheme is …

In this work, we explore a new argumentation pattern in legal discourse, referred to as the
'Argument from Vicarious Liability.'Central to our discussion is the 'Respondeat …